Process intensification and comparison of bioethanol production from food industry waste (potatoes) by ultrasonic assisted acid hydrolysis and enzymatic hydrolysis: Statistical modelling and optimization

Biofuel is one of the promising alternatives for petroleum-based fuels and the bioethanol produced from agricultural residues/industrial wastes are a viable alternative, and current trend in research. In this context, this work reports the utilisation of the waste potatoes (Solanum tuberosum L.) from food industries as precursors for bioethanol. Waste potato mass (WPM) was pre-treated using ultrasonication and hydrolysed using either hydrochloric acid (US-HCl) or alpha-amylase (US-Enzyme). The process conditions such as initial S. cerevisiae concentration (10-20 g/L), enzyme concentration (10-30 U/mL), HCl concentration (1-3% v/v) and ultra-sonication time (5-15 min) were modelled using Box-Behnken RSM design and artificial neural networks (ANN). ANN modelled the experimental data better than RSM which was evident from different errors. Optimum parameters were evaluated using genetic algorithm. The optimal parameters predicted for US-HC1 hydrolysis was 65.8 mg/L at HCl concentration 2.1%, ultra-sonication time 10.7 min, and S. cerevisiae concentration 19.2 g/L with R-2 0.979, whereas, for US-Enzyme hydrolysis was 54.1 g/L at alpha-amylase concentration 25.3 U/mL, ultrasonication time 10.2 min, and S. cerevisiae concentration 19.2 g/L with R-2 0.959. Hence, ultrasonic pretreatment increases the bioethanol yield from waste potatoes and US-HCl process was efficient than the US-Enzyme process.